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| Ethical Analysis and Governance Pathways of Authorship Disputes in Interdisciplinary Research in Digital-Intelligent Era |
| ZHU Shaoyu |
| The Journal of Practical Medicine, 510180, Guangzhou, China |
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Abstract The deep penetration of digital and intelligent technologies has established interdisciplinary research as the core form of knowledge production, injecting momentum into the deep integration in academic publishing while also highlighting disputes regarding research authorship attribution. These authorship disputes erode the foundation of academic integrity and present a significant barrier to the deep development of interdisciplinary research. This paper analyzes 43 cases of interdisciplinary authorship disputes reported by the National Natural Science Foundation of China from 2020 to 2024. The research employs a three-dimensional analytical framework encompassing "institution, technology, and ethics," combined with the CRediT contributor role classification method and blockchain technology, to conduct a comprehensive investigation. The findings reveal that the core contradictions of interdisciplinary authorship disputes are concentrated in three aspects: First, the research paradigm differences between natural sciences (which prioritize empirical data and technological development) and social sciences (which emphasize theoretical construction and ethical analysis) lead to divergent perceptions of contributions, often neglecting implicit contributions such as "interdisciplinary coordination." Second, the lack of unified quantification standards and weight conversion mechanisms for multiple contributions, including technological development and theoretical innovation, leads to difficulties in comparing contributions. Third, interest-driven misuse of authorship rights frequently occurs, including improper behaviors such as "honorary authorship", "guest authorship", ghostwriting and submission, and identity impersonation. The underlying causes manifest at multiple levels: institutionally, there is a lack of exclusive contribution recognition standards and regulatory mechanisms for interdisciplinary research; technically, traditional recording systems are fragmented, and blockchain certification applications lag behind; and ethically, academic ethics are out of order, and the imbalance between scientific research interests and benefits is evident. Consequently, this paper proposes a collaborative governance approach: institutionally, improving the CRediT classification system (adding an interdisciplinary coordination category, refining methodological classification, and establishing a contribution weight conversion mechanism) to standardize contribution recognition, while establishing a full-cycle attribution ethics review system for interdisciplinary projects; technically, building a blockchain-based transparent contribution traceability platform with artificial intelligence-assisted attribution review tools; and ethically, establishing a multi-stakeholder collaborative mechanism involving self-supervision by the academic community, full-process control by publishing institutions, and coordinated punishment by policies and industries. This paper illuminates the distinctive characteristics of interdisciplinary authorship disputes within the Chinese academic ecosystem, providing theoretical support and practical pathways for scientific research management departments to establish specific norms and for academic communities to efficiently resolve authorship disputes. Furthermore, it offers valuable insights for improving the ethical system of academic publishing in the digital and intelligent era while promoting the healthy development of interdisciplinary research.
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Published: 11 December 2025
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| 改造维度 | 具体措施 | 应用场景示例 | | 新增跨学科协调贡献类型 | 定义:设立“跨学科协调”(Interdisciplinary Coordination)分类,涵盖学科语言转译、团队协作管理、研究路径整合等贡献 细分维度: ①学科术语标准化(如医学数据与信息学算法的概念映射) ②跨团队进度协调(如组织医学实验团队与社会科学分析团队的定期研讨) ③研究框架整合(如将工程学模型与人文理论结合的路径设计) | “数字医疗伦理”项目中,协调医学伦理学家与人工智能工程师的沟通工作;跨学科团队中负责将生物学实验数据转化为社会学分析框架的角色 | | 细化方法学贡献分类 | 拆分传统“方法学”(Methodology)为: ①自然科学方法创新(实验设计、数据采集技术等) ②社会科学方法创新(理论模型构建、调研工具开发等) ③跨学科方法融合(如将机器学习算法应用于历史文本分析的方法适配) 要求注明方法适用的学科领域及融合方式 | 计算机科学团队为社会学研究开发的新型网络爬虫工具;经济学团队将医学随机对照试验方法改造为社会政策评估模型 | | 建立学科贡献权重转换机制 | 构建三维量化指标: ①工作量占比(实验次数/理论构建时长等) ②学科稀缺性(如跨学科项目中特殊领域技术的不可替代性) ③成果影响力(如理论创新对多学科的交叉推动作用) 示例转换公式: 自然科学实验贡献值=实验时长×技术复杂度系数 社会科学理论贡献值=理论创新度×学科辐射系数 (注:系数由跨学科伦理委员会根据领域特性设定) | 医学实验团队300小时的细胞培养工作,按技术复杂度系数1.2转换为360单位贡献值;哲学团队提出的跨学科理论框架,按创新度系数1.5转换为225单位贡献值 |
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